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May 1989

Volume 85, Issue S1, pp. S1-S156

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back to top Session G. Underwater Acoustics I: Acoustic Fields
Contributed Papers
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Matched field processing for a moving source (A)

John M. Ozard, Gary H. Brooke, and Scott Tinis

J. Acoust. Soc. Am. Volume 85, Issue S1, pp. S16-S17 (1989); (2 pages)

Online Publication Date: 13 Aug 2005

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The detection or localization of a sound source in a multipath or multimode environment is improved by taking the multipaths into account through matched field processing (MFP). Frequency domain MFP (FDMFP) is very effective for a stationary source. However, there is an implicit averaging over time in FDMFP through the use of the Fourier transform and a further averaging if the covariance matrix is formed. Consequently, if the sound source is moving, the averaging of the time dependent signal will lead to an increase in ambiguity of the source position and a loss in array gain. When the source is moving, the received signal contains information about both source position and source motion. To take full advantage of the information in the time sequence, MFP in the time domain (TDMFP) was implemented. TDMFP is equivalent to obtaining the narrow‐band gain and MFP gain in one step through the use of a Fourier transform modified by the propagation. Simulated results confirm the improved localization and array gain of TDMFP compared to FDMFP for a moving source.
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A stable data adaptive method for matched‐field array processing in acoustic waveguides (A)

C. L. Byrne, R. I. Brent, C. Feuillade, and D. R. DelBalzo

J. Acoust. Soc. Am. Volume 85, Issue S1, pp. S17-S17 (1989); (1 page)

Online Publication Date: 13 Aug 2005

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The presence of a “modal noise” component leads to estimator instability when Capon's maximum likelihood (ML) method is applied to the processing of data from a vertical array in an acoustic waveguide. The physics of the waveguide forces signal vectors and noise vectors alike to be projected onto the span of the “mode” vectors, when the number of sensors (N) exceeds the number of propagating modes (M). The instability occurs whenever the (single snapshot) N × 1 data vectors have the form x  =  Us + Uγ + white noise, where the matrix U is N × M (sampling the normal modes at the hydrophone locations and independent of the actual acoustic disturbances present), and s and γ correspond to signal and ambient noise sources, respectively. This condition arises in normal‐mode and local normal‐mode propagation. The dominant eigenvectors of R−1 (where R is the cross‐spectral matrix) are sensitive to slight inaccuracies in the calculation of R−1 in ways that affect the performance of the ML estimator. Following transformation of the N × N matrix R to the M × M modal space cross‐spectral matrix T, Capon′s method is applied to T to obtain the “reduced maximum likelihood” (RML) estimator. This procedure, which is a development of the sector focused stability technique of Steele and Byrne [Proceed. ISSPA 87, 24–28 August 1987, Brisbane, Australia, pp. 408–412], largely eliminates instabilities due to inaccurate inversion of R. Simulations are presented for a shallow‐water environment to provide comparison between the ML and the RML estimators. These indicate that the degree of instability depends upon the level of noise (both correlated noise and white noise) and that a significant improvement in performance can be expected by use of the RML estimator in both cases.
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A symmetry renormalization method for matched‐mode sidelobe reduction (A)

George B. Smith and George M. Frichter, IV

J. Acoust. Soc. Am. Volume 85, Issue S1, pp. S17-S17 (1989); (1 page)

Online Publication Date: 13 Aug 2005

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Current matched‐field research at NORDA is centered on techniques that attempt to match measured and predicted modal amplitudes for improved detection and localization of acoustic sources in shallow‐water waveguides. Ambiguity functions generated by these modal estimators display a sidelobe structure that is symmetric about the true source peak. This symmetry represents additional information about the signal location, which can be used to further enhance detection. Here, a simple correlation algorithm is presented which enhances the signal peak and suppresses sidelobes by renormalizing each point of the ambiguity function in accordance with the symmetry around that point. Since a renormalized ambiguity function retains the range symmetry of the original, the technique can (within limits) be applied iteratively. Computer simulations of a shallow‐water Pekeris waveguide are used to demonstrate the effectiveness of renormalization when applied to both narrow‐band and frequency‐averaged mode matching.
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Source localization: Matched field versus matched mode Synthetic and real data performance analysis (A)

Sergio M. Jesus and Rachel M. Hamson

J. Acoust. Soc. Am. Volume 85, Issue S1, pp. S17-S17 (1989); (1 page)

Online Publication Date: 13 Aug 2005

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The present study compares the matched field and the matched mode techniques for passively localizing a narrow‐band point source in a shallow‐water, range‐independent environment. The matched mode technique is fully characterized in terms of sidelobe ambiguity performance and robustness against both system and environment parameter variation and mismatch. Comparative results are also shown for real data detection of a cw source immerged at different depths in a 120‐m depth channel using a 62‐m aperture vertical array. The results of this study indicate that the matched mode method is much less sensitive to the environmental conditions than the matched field method, and in particular, the result is less degraded by the effects of partial water column sampling (short array). Results obtained on real data showed good agreement with the corresponding tests from simulated data. However, a large sidelobe coverage was found for some situations leading to detection losses. Major causes of performance degradation are the uncertainty on the array sensor position due to array motion and correlated noise due, mainly, to surface‐generated noise.
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Broadband acoustic‐field simulations from standard ray theory (A)

Stanley M. Flatté, John Colosi, Timothy F. Duda, Galina Rovner, and Jan Martin

J. Acoust. Soc. Am. Volume 85, Issue S1, pp. S17-S17 (1989); (1 page)

Online Publication Date: 13 Aug 2005

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The complete wave field over a small region around 1000 km from a pulsed source is reconstructed in two ways. First, all the rays from the source to a vertical array of receivers at 1000 km are found, along with their travel times, number of caustics, arrival angles, and intensities. The pattern of wave fronts in a space at a given time is then reconstructed on a closely spaced grid surrounding 1000 km by treating these rays in an appropriate way. Second, the parabolic equation method is used at multiple frequencies to synthesize a pulse. The two fields are compared. Finally, the effect of internal waves is simulated by use of the first method, introducing random fluctuations on the travel times and arrival angles of each ray. [Work supported by ONR, Code 1125OA.]
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Acoustic wave front distortions at long ranges from internal waves (A)

Timothy F. Duda and Stanley M. Flatté

J. Acoust. Soc. Am. Volume 85, Issue S1, pp. S17-S17 (1989); (1 page)

Online Publication Date: 13 Aug 2005

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In the absence of small‐scale variations on sound speed in the ocean, a pulsed source delivers a series of smooth wave fronts onto a vertical array at long range from the source (multiray propagation). Small‐scale variations such as internal waves induce distortions on the wave fronts with transverse correlation function determined by the phase‐structure function, which is itself calculable by integrating appropriate functions along the trajectory of an undistorted ray. Expressions for the phase‐structure function at small separations have been previously given in the form of arrival‐angle spreads due to internal waves, but these expressions are only for vertical receiver separations up to about 100 m. Evaluations of the phase‐structure function for separations up to several kilometers are presented, and particular realizations of wave front distortions that result from these internal‐wave effects are shown. [Work supported by ONR, Code 1125OA.]
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Preliminary results from the 1988 Monterey Bay acoustic tomography experiment (A)

James H. Miller, James F. Lynch, and Ching‐Sang Chiu

J. Acoust. Soc. Am. Volume 85, Issue S1, pp. S18-S18 (1989); (1 page)

Online Publication Date: 13 Aug 2005

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An ocean acoustic tomography experiment was held 12–16 December 1988 near Monterey, California. The objectives of this experiment were to test a tomographic system to analyze the effects of ocean surface waves, internal waves, and complex three‐dimensional bathymetry on long‐range acoustic propagation. An acoustic source with a center frequency of 224 Hz and source level of 177 dB was placed on a seamount 30 km off Point Sur. Seven modified sonobuoys (with anchor, bottom‐mounted hydrophones, large capacity batteries, and large floats) were placed in Monterey Bay to receive the acoustic signals at ranges of 35 to 60 km from the source. The sonobuoy rf signals were received, demodulated, and the acoustic data were recorded on shore. Oceanographic measurements were taken (for comparison with the acoustically derived results) with a surface wave frequency‐directional spectra buoy, surface wave frequency spectra buoys, CTD yo‐yo's for internal wave spectra, ADCP, and conventional hydrographic survey for sound‐speed profiles. Preliminary analyses and comparison of the acoustic and oceanographic measurements will be presented. An outline of what the complete analysis will entail will also be presented. [Work supported by ONR and Naval Postgraduate School Research Council.]
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Sound‐speed determination using matched field processing techniques (A)

C. Karangelen and O. Diachok

J. Acoust. Soc. Am. Volume 85, Issue S1, pp. S18-S18 (1989); (1 page)

Online Publication Date: 13 Aug 2005

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Matched field processing is shown to be effective for estimating sound speed in a deep, range‐independent ocean environment. The amplitude and phase of signals from a distant source measured on a large aperture vertical array are sensitive to changes in sound speed. This sensitivity is exploited to infer the environmental sound‐speed profile by matching predicted and measured amplitude and phase. A sound‐speed profile model is developed based on a modified version of Munk's canonical sound field equation. This model is used to determine sound‐speed profile using a 15‐Hz signal from a 240‐m explosive source detected on a 675‐m vertical array at a range of 50 km in a deep‐water Pacific environment, characterized by a classical range‐independent sound channel at 700 m. The search for the best estimated profile is conducted by varying the sound channel axis strength and depth in the modified Munk equation while maintaining a constant sound‐speed profile at great depths. Differences between the estimated and measured profiles are less than ± 2 m/s; the sound channel axis depth is determined within 20 m of the measured axis depth. Extension of this approach to include mesoscale features and greater range is discussed.
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Localization schemes for beam‐type sources (A)

I. T. Lu

J. Acoust. Soc. Am. Volume 85, Issue S1, pp. S18-S18 (1989); (1 page)

Online Publication Date: 13 Aug 2005

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A time‐harmonic isotropic source in stratified waveguides can be localized by performing matched‐field processing in “mode space.” Because the range and depth information of the source are contained only in the phase and magnitude, respectively, of complex model amplitudes, the range and depth data can be processed independently. This is not true for beam‐type sources. When propagating in a waveguide, an initially collimated beam undergoes diffusion after successive reflections and refractions and is converted eventually into the oscillatory pattern of one or more guided modes. However, the upgoing and downgoing plane wave constituents of a given mode do not have the same excitation strength as in the case of isotropic sources. Here, localization schemes of a Gaussian beam source that is modeled via the complex source point technique are considered. The beam direction, beam width parameter, and waist location are determined in “mode space.” The procedure is greatly simplified if the source is a well‐collimated beam. [Work supported by NSF.]
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Source localization by inversion of the parabolic equation method (A)

Susan M. Bates and Bruce J. Bates

J. Acoust. Soc. Am. Volume 85, Issue S1, pp. S18-S18 (1989); (1 page)

Online Publication Date: 13 Aug 2005

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The inverse split‐step parabolic equation method is derived. Spatial localization of single and multiple low‐frequency harmonic point sources in a deep ocean is demonstrated by using simulated pressure field measurements from a vertical array. In addition, the method is applied to a source extended in range and depth. This method is solved in a single iteration, unlike some inverse techniques that vary parameters.
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